Lead Data Scientist

Nike • Beaverton, OR

1d

About The Position

The Lead Data Scientist advances state-of-the-art recommendation systems at the intersection of machine learning, optimization, generative AI, and decision intelligence. The role develops solutions that help customers and partners discover relevant products, optimize assortments, and make informed purchasing decisions through personalized, data-driven experiences at scale.

The role leads the scientific strategy and technical execution for AI-powered recommendations across predictive modeling, recommendation systems, optimization engines, and generative AI experiences. It calls for someone who can translate ambiguous business needs into production-ready systems and lead cross-functional teams spanning data science, AI/ML engineering, product management, and user experience.

Requirements

• Master’s degree in Computer Science, Operations Research, Statistics, Applied Mathematics, Engineering, or a related field; suitable combinations of education, experience, or training will be accepted.
• At least 5 years of experience leading the design, development, and deployment of data science, machine learning, optimization, and operations research models at scale.
• Strong proficiency in Python and experience with machine learning frameworks such as PyTorch or TensorFlow.
• Deep knowledge of recommendation systems, ranking models, personalization, and predictive analytics.
• Experience designing and evaluating large-scale experimentation platforms and A/B testing methodologies.
• Experience building solutions using Agentic AI, large language models (LLMs), tool orchestration, and automated and human-in-the-loop evaluation of Agentic systems.
• Demonstrated expertise in modern recommender systems and emerging LLM/GenAI techniques, including the ability to lead scalable personalization solutions that combine recommendation methods, embeddings, semantic retrieval, ranking, and generative approaches.
• Experience with cloud-native ML platforms such as Databricks or AWS SageMaker.
• Demonstrated ability to lead complex cross-functional initiatives.
• Strong communication skills.

Nice To Haves

• Strong background in optimization techniques, including linear programming, mixed-integer optimization, reinforcement learning, and multi-objective optimization.

Responsibilities

• Develop and deploy advanced recommendation models that deliver personalized product experiences aligned with customer needs and partner business objectives.
• Design and implement optimization frameworks that balance customer preferences, inventory availability, profitability, and operational constraints.
• Lead the development of generative AI capabilities that enhance recommendation experiences through intelligent insights, explanations, and decision support.
• Establish experimentation and measurement frameworks to evaluate recommendation quality, customer engagement, business impact, and AI effectiveness.
• Partner with product managers, engineers, designers, and business stakeholders to define strategy, prioritize opportunities, and execute the product roadmap.
• Drive scientific rigor through model evaluation, offline benchmarking, online experimentation, and continuous improvement.
• Mentor and develop data scientists and machine learning engineers, fostering technical excellence and a culture of learning.
• Communicate complex analytical findings and strategic recommendations to technical and non-technical audiences, including senior leadership.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior